Data Governance Lead at HCL AMERICA INC. in Location not listed

Job Summary

The Module Prints project focuses on using Artificial Intelligence to automatically extract relevant technical information from engineering diagrams and module prints. The solution applies computer vision and machine learning techniques to identify components, annotations, dimensions, labels, and other engineering-specific information contained within complex drawings. The goal is to convert traditionally unstructured visual engineering data into structured, searchable information that can be used by downstream applications and engineering teams. Key skills involved in this project include computer vision, image processing, machine learning algorithms, object detection, and AI-based information extraction

Key Responsibilities

The Intelligent Document Intelligence (IDI) project uses AI to extract and interpret information from complex PDF documents related to vehicle accidents. The system is designed to identify important details such as the vehicles involved, accident location, crash site information, potential causes of the accident, contributing factors, and other relevant incident data. AI-based document understanding techniques are used to process both textual and visual content within PDFs and transform the extracted information into structured data for further analysis. Key technologies include document AI, natural language processing, computer vision, machine learning, OCR, and intelligent information

Skill Requirements

This project involves developing an intelligent AI agent that assists engineers in creating and improving requirements within Codebeamer. The agent analyzes existing requirement statements, associated documentation, engineering diagrams, and relevant organizational knowledge to identify missing information, improve clarity, and enrich requirements with additional technical context. Advanced Retrieval-Augmented Generation (RAG) techniques can be used to retrieve relevant historical requirements, standards, specifications, and supporting documentation before generating recommendations. Computer vision capabilities can also enable the agent to understand diagrams and other visual engineering artifacts associated with a requirement. Key skills include advanced RAG architectures, AI agents, large language models, computer vision, semantic search, vector databases, prompt engineering, and enterprise knowledge integration